102,528 research outputs found
Cognitive Bias Modification for Depression
No full textChapter titled, "Cognitive Bias Modification for Depression" written by Christopher G. Beevers, Mary E. McNamara, Mackenzie Zisser, and Rachel L. Weisenburger for a forthcoming book, APA Handbook of Depression, edited by Jeremy Pettit and Thomas Olino
Pre-print for "Change in Negative Attention Bias Mediates the Association BetweenAttention Bias Modification Training and Depression Symptom Improvement"
No full textPre-print for manuscript titled "Change in Negative Attention Bias Mediates the Association Between Attention Bias Modification Training and Depression Symptom Improvement" by Christopher G. Beevers, Kean J. Hsu, David M. Schnyer, Jasper A.J. Smits, & Jason Shumake to appear in the Journal of Consulting and Clinical Psycholog
Issues of partial credit in mathematical assessment by computer
No full textThe CALM Project for Computer Aided Learning in Mathematics has operated at Heriot‐Watt University since 1985. From the beginning CALM has featured assessment in its programs (Beevers, Cherry, Foster and McGuire, 1991), and enabled both students and teachers to view progress in formative assessment The computer can play a role in at least four types of assessment: diagnostic, self‐test, continuous and grading assessment. The TLTP project Mathwise employs the computer in three of these roles. In 1994 CALM reported on an educational experiment in which the computer was used for the first time to grade, in part, the learning of a large class of service mathematics students (Beevers, McGuire, Stirling and Wild ,1995), using the Mathwise assessment template. At that time the main issues identified were those of ‘partial credit’ and communication between the student and the computer. These educational points were addressed in the next phase of the CALM Project in which the commercial testing program Interactive PastPapers was developed. The main aim of this paper is to describe how Interactive Past Papers has been able to incorporate some approaches to partial credit which has helped to alleviate student worries on these issues. Background information on other features in Interactive Past Papers is also included to provide context for the discussion
Analysis code for manuscript and supplemental materials
No full textAnalysis code used in manuscript: Self-referent encoding and depression symptoms: An intensive sampling approach by Rachel L. Weisenburger, Justin Dainer-Best, Mackenzie Zisser, Mary E. McNamara, Christopher G. Beever
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Dysfunctional Attitude Scale - Short Forms 1 & 2
No full textShort form of the Dysfunctional Attitude Scale (versions 1 and 2) that were created as part of this publication: Beevers, C. G., Strong, D. R., Meyer, B., Pilkonis, P. A., & Miller, I. R. (2007). Efficiently assessing negative cognition in depression: An item response theory analysis of the Dysfunctional Attitude Scale. Psychological Assessment, 19(2), 199–209. https://doi.org/10.1037/1040-3590.19.2.199Psycholog
Using network analysis to identify central symptoms of adolescent depression
No full textObjective: Experiencing depression symptoms, even at mild to moderate levels, is associated with maladaptive outcomes for adolescents. We used network analysis to evaluate which symptoms (and associations between symptoms) are most central to adolescent depression.
Method: Participants were part of a large, diverse community sample (N = 1,409) of adolescents between the ages of 13-19 years old. Network analysis was used to identify the most central symptoms (nodes) and associations between symptoms (edges) assessed by the Children’s Depression Inventory (CDI). We also evaluated these centrality indicators for network robustness using stability and accuracy tests, associated symptom centrality with mean levels of symptoms, and examined potential differences between the structure and connectivity of depression networks in boys and girls.
Results: The most central symptoms in the network were self-hatred, loneliness, sadness, and pessimism. The strongest associations between symptoms were sadness-crying, anhedonia-school dislike, sadness-loneliness, school work difficulty-school performance decrement, self-hatred-negative body image, sleep disturbance-fatigue, and self-deprecation-self-blame. The network was robust to stability and accuracy tests. Notably, symptom centrality and mean levels of symptoms were not associated. Boys and girls’ networks did not differ in levels of connectivity, though the link between body image and self-hatred was stronger in girls than boys.
Conclusions: Self-hatred, loneliness, sadness, and pessimism were the most central symptoms in adolescent depression networks, suggesting these symptoms (and associations between symptoms) should be prioritized in theoretical models of adolescent depression and could also serve as important treatment targets for adolescent depression interventions
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Serotonin transporter gene variation and its association with cognitive vulnerability to depression
No full texttextDepression is a serious condition that affects a significant proportion of the population and causes substantial life impairment (Kessler et al., 2003). Cognitive models of depression vulnerability (e.g., Teasdale, 1988) posit that information processing biases for negative and positive stimuli play a critical role in the disorder. Change in negative thinking in response to dysphoric moods is referred to as cognitive reactivity and has been shown to be a risk factor for future increases in depression (e.g., Beevers & Carver, 2003; Segal et al., 2006). Interestingly, recent behavioral genetics research indicates that certain genes may influence cognitive factors associated with depression. The short allele of a polymorphism of the serotonin transporter gene (5-HTTLPR) has been associated with increased risk for depression in the context of life stress (Caspi et al., 2003); however, the psychological mechanisms that increase depression risk for short 5-HTTLPR allele-carriers have not been definitively identified. Recent work has begun to reveal an association between the 5-HTTLPR and cognitive factors associated with depression such as attention bias for emotional information (Beevers et al., 2007) and negative thinking style (Hayden et al., 2007). A pilot study (n = 156) revealed an association between 5-HTTLPR and cognitive reactivity for attention bias for happy faces. The current study (n = 180) extended and improved upon the pilot study’s methodology and examined the relationship between the 5-HTTLPR and cognitive reactivity for attention to sad and happy faces as well as cognitive reactivity for dysfunctional attitudes. Cognitive variables were assessed after a neutral mood induction and after a sad mood induction at two laboratory sessions separated by at least 24 hours. There was a significant association between the 5-HTTLPR and cognitive reactivity for attention bias for emotional faces among Caucasian participants. Specifically, the short allele was associated with increased bias for emotional faces after the sad mood induction compared to the neutral mood induction. There was a linear relationship between number of short alleles possessed by participants and increase in bias for emotional information. The 5-HTTLPR was not significantly associated with cognitive reactivity for dysfunctional attitudes, but the effect was in the expected direction. Results are discussed in the context of recent neuroimaging research and plasticity models of behavior genetics. Implications for a model of depression vulnerability integrating genetic, neural, and cognitive factors and future directions for similar behavioral genetics studies are discussed.Psycholog
Specificity and overlap of attention and memory biases in depression
No full textAttentional and memory biases are viewed as crucial cognitive processes underlying symptoms of depression. However, it is still unclear whether these two biases are uniquely related to depression or whether they show substantial overlap. We investigated the degree of specificity and overlap of attentional and memory biases for depressotypic stimuli in relation to depression and anxiety by means of meta-analytic commonality analysis. By including four published studies, we considered a pool of 463 healthy and subclinically depressed individuals, different experimental paradigms, and different psychological measures. Memory bias is reliably and strongly related to depression and, specifically, to symptoms of negative mood, worthlessness, feelings of failure, and pessimism. Memory bias for negative information was minimally related to anxiety. Moreover, neither attentional bias nor the overlap between attentional and memory biases were significantly related to depression. Limitations include cross-sectional nature of the study. Our study showed that, across different paradigms and psychological measures, memory bias (and not attentional bias) represents a primary mechanism in depression
Bibliographie Hilarion G. Petzold 1958 – 2009 mit Anhang als Einführung
No full textDieses Archiv enthält die Gesamtbibliographie der Werke des Autors nebst einiger Texte „Über H. G. Petzold“ im Schlussteil der Bibliographie sowie einen Anhang mit einer Einführung in die Architektur des Werkes in seinem wissenslogischen Aufbau als Ausarbeitung seines „Tree of Science Modells“ (2007).This archive contains the complete bibliography of the author and some texts about H. G. Petzold, moreover an epilogue with an introduction to the architecture of the works in its epistemological structure and composition and as an elaborations of Petzold’s „Tree of Science Modell (2007).https://www.fpi-publikation.de/polyloge/01-2009-petzold-h-g-gesamtbibliographie-h-g-petzold-1958-2009-updating-november2009/peerReviewedpublishedVersio
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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